Breast cancer is a multigenic disease with a genetic etiology that is in part composed of low-penetrance, high frequency modifier genes. Alleles of these genes can act to increase resistance or sensitivity to breast cancer. The long-term goal of this project is to both models the complexity of the genetic component of breast cancer etiology and to identify and characterize breast cancer resistance modifier genes. Using a rat model, 4 susceptibility loci (Mcs1-4) were genetically identified in the Cop rat. Mcs1 was found to have 3 sub-loci, each contributing to resistance. The locations of 2 sub-loci, Mcs1a and Mcs1c, have been mapped to approximately 1 Mb each. The current proposal focuses on these 2 sub-loci. It is proposed to fine-map modifier genes at these sub-loci to approximately 0.5 Mb using recombinant congenic rats. Next, genes and regulatory sequences in these intervals will be identified using the nearly finished rat sequences of these genomic regions. Potential genes will be resequenced in Cop and WF rats and gene expression will be quantified. This approach has thus far identified 1 candidate at each locus. Additional candidates will be sought. Selected candidate genes will be evaluated by producing and characterizing transgenic or knockout rats. In addition, Mcs1a and Mcs1c will be functionally evaluated using a variety of assays on congenic rats. Cell autonomy will be evaluated using a transplantation assay, differential gene expression will be characterized using DMA arrays, and the range of Mcsla and Mcslc activity will be estimated by challenging congenic rats with other carcinogens and the Neu oncogene. It is anticipated that results of this project will identify 2 rat mammary cancer resistance genes. This will allow us in the future to determine whether homologous human genes also have alleles that modify breast cancer risk. If so, this new knowledge will provide both prognostic markers of breast cancer risk and targets for development of chemoprevention drugs. Knowledge of these genes and their function will provide unique insights into the etiology of breast cancer.